Influence of Role Models and Mentors on Female Graduate Students’ Choice of Science as a Career

The purpose of this study was to examine the source, nature, and degree of influence of role models and mentors on female graduate students’ choice of science as a career. Also examined was the existence of gender or area-of-study (engineering, biological science, physical sciences) differences. Results of a factor analysis of the Influence of Others on Academic and Career Decisions Scale (IOACDS, Nauta & Kokaly, 2001) demonstrated that role models and mentors influenced students in distinct ways. Significant gender, area-of-study, and undergraduate country differences were found

A LONGITUDINAL STUDY OF THE INFLUENCE OF A STEM CAREER PLANNING COURSE AND PERCEIVED STRESS ON CAREER SEARCH SELF-EFFICACY AND RETENTION IN ENGINEERING UNDERGRADUATE STUDENTS

This study investigated a) the influence of a STEM career planning course on undergraduate engineering students’ career search self-efficacy, b) the influence of perceived stress on building students’ career search self-efficacy, and c) the relationship career search self-efficacy had in predicting students’ odds of persistence in an engineering major. The researcher analyzed students’ week 1, week 6, and week 14 scores of career search self-efficacy and perceived stress. Data were collected from the Spring 2019 and Fall 2019 cohorts of a STEM career planning. As a result, the analysis included (N = 286) undergraduate engineering students. Repeated measures multilevel models and a logistic regression were analyzed in order to answer the study’s research questions. The results suggested that after accounting for perceived stress, students’ career search self-efficacy increased over the semester in a STEM career planning course. Further, perceived stress was a significant negative predictor of career search self-efficacy scores over the course of the semester and career search self-efficacy was a significant positive predictor of students’ increased odds of persisting in an engineering major. An exploratory analysis revealed that there were no changes in career search self-efficacy scores based on demographic variables including race, gender, ethnicity, and first-generation status. However, another multilevel model analysis yielded a statistically significant positive relationship between career advising ratings and career search self-efficacy scores. Overall, the results of the study support STEM career planning courses as impactful interventions for undergraduate students. Implications for future research; school and career counselors; and counselor education are discussed

How to Do QuantCrit: A Reflexive Account of Applying Critical Quantitative Methods to a Study of Black Women in STEM

There has been extensive research into the underrepresentation of minoritized students in STEM disciplines since the 1990s with limited success in improving the representation of Black women in math-intensive STEM fields. This dissertation aims to address how the guiding tenets of critical quantitative (QuantCrit) methods work when used with publicly available datasets and commonly used statistical approaches. Additionally, this dissertation provides a framework for how to apply reflexivity as a method while utilizing a QuantCrit approach. The publicly available HSLS:09 dataset is used as part of a reflexive study to demonstrate how the tenets of Critical Race Theory (CRT) map onto a QuantCrit study utilizing structural equation modeling. Through personal, methodological, and conceptual reflexivity, disconnects between the tenets and the QuantCrit study are highlighted and discussed. These findings indicate a need for more robust guidelines surrounding QuantCrit research. Furthermore, publication access must be expanded to encourage movement beyond traditional White ways of knowing. Advisor: Elvira Abric

College Students’ Persistence and Degree Completion In Science, Technology, Engineering, and Mathematics (STEM): The Role Of Non-Cognitive Attributes Of Self-Efficacy, Outcome Expectations, And Interest

The lack of students’ persistence (or student’s effort to continue their academic studies until degree completion) in Science, Technology, Engineering, and Mathematics (STEM) and the attrition of STEM students as well as the shortage of STEM workers have gathered much attention from policy makers, governmental agencies, higher education researchers and administrators in recent years. As a result, much research efforts have been directed towards identifying factors causing the leaks in the STEM pipeline and finding effectively antidotes to patch the leakage points along the pipe. In the past, most studies in the STEM disciplines have focused on individual cognitive capacities (or academic predictors) such as precollege performance indicators (e.g., high school GPA) and standardized achievement test scores (e.g., SAT and ACT) to explain the leading factors contributing to the high attrition rate among STEM college students. Yet these studies just address mainly one aspect of the key reasons why students failed to persist. We still lack evidence, both empirically and theoretically, on how “non-cognitive skills”—which are essential individual characteristics vital for success in any schooling, work, and other life-time outcomes— may influence STEM major persistence. Absent from most of the scholarly discussions are the many ways in which psychosocial factors (such as grit, tenacity, optimism, self-efficacy, perseverance, motivation, self-discipline, teamwork, reliability) influence the decision-making processes of students’ persistence. Rather than focusing on the traditional cognitive ability and academic achievement measures of academic preparation this study focused on psychosocial factors that influence the decision-making processes of students’ persistence and degree completion. The purpose of the study is to examine the extent to which non-cognitive factors (i.e., self-efficacy, outcome expectation, and interest) contribute to undergraduate students’ persistence and college degree completion in STEM with particular attention to students enrolled in 4-year colleges and universities in the United States. The analytical sample for this study was drawn from the Educational Longitudinal Study (ELS:2002-2012) dataset with the final sample used for analysis representing the 2002 cohort of 10th graders who declared STEM major in college by 2006 and participated in the final wave of ELS in 2012. As such, the result was reflective of this group of students, and not all STEM students in college in general. Result of the study revealed three general findings about the three noncognitive factors. First, students with strong interest in pursuing a STEM major, a high sense of self-efficacy, and a mid to high level of outcome expectations are more likely to persist and complete their college degree in their declared major in STEM field. Students who reported that they had no interest in pursuing a STEM major yet declared a STEM major in their postsecondary education, and who have moderate to high self-efficacy and high outcome expectations are more likely to switch to a non-STEM major and persist to complete a degree in a non-STEM field. Thirdly, irrespective of whether the student was interested in pursuing STEM, a student with low self-efficacy and low outcome expectations was more likely to not attain any degree or credential

College Students’ Persistence and Degree Completion In Science, Technology, Engineering, and Mathematics (STEM): The Role Of Non-Cognitive Attributes Of Self-Efficacy, Outcome Expectations, And Interest

The lack of students’ persistence (or student’s effort to continue their academic studies until degree completion) in Science, Technology, Engineering, and Mathematics (STEM) and the attrition of STEM students as well as the shortage of STEM workers have gathered much attention from policy makers, governmental agencies, higher education researchers and administrators in recent years. As a result, much research efforts have been directed towards identifying factors causing the leaks in the STEM pipeline and finding effectively antidotes to patch the leakage points along the pipe. In the past, most studies in the STEM disciplines have focused on individual cognitive capacities (or academic predictors) such as precollege performance indicators (e.g., high school GPA) and standardized achievement test scores (e.g., SAT and ACT) to explain the leading factors contributing to the high attrition rate among STEM college students. Yet these studies just address mainly one aspect of the key reasons why students failed to persist. We still lack evidence, both empirically and theoretically, on how “non-cognitive skills”—which are essential individual characteristics vital for success in any schooling, work, and other life-time outcomes— may influence STEM major persistence. Absent from most of the scholarly discussions are the many ways in which psychosocial factors (such as grit, tenacity, optimism, self-efficacy, perseverance, motivation, self-discipline, teamwork, reliability) influence the decision-making processes of students’ persistence. Rather than focusing on the traditional cognitive ability and academic achievement measures of academic preparation this study focused on psychosocial factors that influence the decision-making processes of students’ persistence and degree completion. The purpose of the study is to examine the extent to which non-cognitive factors (i.e., self-efficacy, outcome expectation, and interest) contribute to undergraduate students’ persistence and college degree completion in STEM with particular attention to students enrolled in 4-year colleges and universities in the United States. The analytical sample for this study was drawn from the Educational Longitudinal Study (ELS:2002-2012) dataset with the final sample used for analysis representing the 2002 cohort of 10th graders who declared STEM major in college by 2006 and participated in the final wave of ELS in 2012. As such, the result was reflective of this group of students, and not all STEM students in college in general. Result of the study revealed three general findings about the three noncognitive factors. First, students with strong interest in pursuing a STEM major, a high sense of self-efficacy, and a mid to high level of outcome expectations are more likely to persist and complete their college degree in their declared major in STEM field. Students who reported that they had no interest in pursuing a STEM major yet declared a STEM major in their postsecondary education, and who have moderate to high self-efficacy and high outcome expectations are more likely to switch to a non-STEM major and persist to complete a degree in a non-STEM field. Thirdly, irrespective of whether the student was interested in pursuing STEM, a student with low self-efficacy and low outcome expectations was more likely to not attain any degree or credential

Education Research Using Data Mining and Machine Learning with Computer Science Undergraduates

In recent decades, we are witness to an explosion of technology use and integration of everyday life. The engine of technology application in every aspect of life is Computer Science (CS). Appropriate CS education to fulfill the demand from the workforce for graduates is a broad and challenging problem facing many universities. Research into this ‘supply–chain’ problem is a central focus of CS education research. As of late, Educational Data Mining (EDM) emerges as an area connecting CS education research with the goal to help students stay in their program, improve performance in their program, and graduate with a degree. We contribute to this work with several research studies and future work focusing on CS undergraduate students relating to their program success and course performance analyzed through the lens of data mining. We perform research into student success predictors beyond diversity and gender. We examine student behaviors in course load and completion. We study workforce readiness with creation of a new teaching strategy, its deployment in the classroom, and the analysis shows us relevant Software Engineering (SE) topics for computing jobs. We look at cognitive learning in the beginning CS course its relations to course performance. We use decision trees in machine learning algorithms to predict student success or failure of CS core courses using performance and semester span of core curriculum. These research areas refine pathways for CS course sequencing to improve retention, reduce time-to–graduation, and increase success in the work field

Factors That Contribute to Persistence and Retention of Underrepresented Minority Undergraduate Students in Science, Technology, Engineering, and Mathematics (STEM)

The objective of this research was to identify specific factors that contribute to underrepresented minority (African American, Hispanic, Native American) undergraduate students‟ success in STEM disciplines at a regional university during the 2007-2010 timeframe. As more underrepresented minority (URM) students complete STEM degrees, many will possess the skills to become part of the domestic human capital needed to meet U. S. workforce demands and enhance the nation‟s STEM innovation. According to Burke and Mattis (2007), the lack of URM students in STEM education and in the workforce is one of the major contributors to STEM shortages in the United States. In this study, the investigator employed a sequential mixed method design to comprehensively examine which specific factors contributed to URM student success in STEM. Mixed methods design was necessary in order to capture the complexities of factors contributing to URM persistence and retention in STEM disciplines. Data collection and analysis was conducted to address four research objectives in two distinct sequential phases. In Phase I, quantitative analysis of archival data (taken from the regional university‟s ISIS and SAM databases) was used to explore the impact of specific factors on URM student persistence and retention. Logistic regression was used as the statistical procedure to examine objectives one and two. In Phase II, qualitative data were collected and analyzed using a nominal group technique. The researcher met with eighteen URM students (11 African American, four Hispanics, and three Native American) and posed two questions based on the quantitative findings as to why they persisted and were retained in STEM disciplines. This study was designed to help students and this institution better understand how URM students can navigate and overcome barriers to obtaining STEM degrees. According to George, Neale, Van Horne, and Malcolm (2001), tapping the reservoir of URM could help in meeting the STEM workforce demand as these minorities continue to show great increases in college enrollment. The findings for objectives one and two revealed four factors that were statistically significant contributors of URM student success in STEM disciplines. They included college GPA, academically rigorous curriculum, percent of hours completed, and percent of hours passed. The findings of objectives three and four revealed the top five rankings of URM persistence and retention factors in STEM success. The researcher employed a nominal group technique to collect and analyze this qualitative data

Persistence in STEM: Development of a Persistence Model Integrating Self-efficacy, Outcome Expectations and Performance in Chemistry Gateway Courses

STEM persistence has been an important issue, especially in the context of underrepresented groups based on race and gender. Researchers in the last decade or so have been examining the powerful impact that affective and cognitive factors can exert individually on performance and persistence. It is only reasonable to hypothesize that combining affective and cognitive measures would offer a more thorough understanding of factors that impact students’ performance and STEM persistence. Evaluating these outcomes in the context of gateway courses is particularly essential due to the non-negligible percentage of students who drop out of these courses or decide to change their intended STEM majors after key testing events. Using social cognitive career theory (SCCT) as a framework, this exploratory study set out to develop / adapt surveys to capture two key SCCT constructs – self-efficacy (SE) and outcome expectations (OE). These surveys were psychometrically tested and used in the development of cross-sectional predictive performance and persistence models for general chemistry. Items from both full-length surveys were subsequently used in the development of a shortened survey, which was administered as key points during a semester to evaluate changes in performance, SE or OE prior to or after testing events. Interventions, packaged as study tools, were also administered to students before these events; the impact of these study tools on students’ SE, OE and performance was also assessed in efforts to assemble preliminary profiles for at-risk students

The Relationship Between Undergraduate Research Training Programs and Motivational Resources for Underrepresented Minority Students in STEM: Program Participation, Self-efficacy, a Sense of Belonging, and Academic Performance

Although calls for a more diverse workforce in biomedical fields have been widespread, racial and ethnic gaps in biomedical degree attainment persist. In order to succeed, URM STEM students must persevere despite numerous challenges and stay continuously motivated on the long road to degree attainment in biomedical disciplines. Past higher education research has identified two key self-appraisals, a sense of belonging and self-efficacy, as crucial for student success. These beliefs, which can serve as motivational resources for students, include students\u27 convictions about whether they are a valued member of their academic community and whether they have what it takes to succeed in their discipline. This study explored how participation in an undergraduate research training program and students\u27 motivational resources may be shaping their academic performance and thus contributing to their successful completion of undergraduate biomedical degrees. The study also dissected program participation into five components and explored whether a sense of belonging or self-efficacy played a mediational role in the relationship between program participation and academic performance for URM STEM students. Single and multiple linear regression analyses were used and results indicated significant links between overall program participation and both motivational resources as well as significant connections between various program components and these self-perceptions. No significant relationship surfaced between overall program participation and academic performance but in a multiple regression analysis, research dosage was linked to performance for students in the study. Additionally, no significant connection was found between the motivational resources and academic performance and thus, the mediational role of a sense of belonging and self-efficacy in the relationship between program participation and performance could not be tested

Integrated STEM and STEM Partnerships: Teaching and Learning

The overall focus of this Special Issue is on educational spaces relating to integrated STEM and interdisciplinary partnerships that might occur in integrated STEM spaces. These educational spaces include formal and informal schooling and include studies involving collaborative work teams, pre-service, in-service teachers, STEM faculty experiences, pre-collegiate students, interdisciplinary education, science education, technology education, engineering and computer science education, and mathematics education. The purpose of this Special Issue is to bring together a showcase of current studies in integrated STEM and related partnership work in teaching and learning. The newly released Handbook of Research on STEM Education (Johnson, Mohr-Schroeder, Moore, and English, 2020) explores areas of STEM in an international context and sets the stage for this Special Issue. The articles included show perspectives from around the globe